Instructions to use suno/bark-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use suno/bark-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="suno/bark-small")# Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("suno/bark-small") model = AutoModelForTextToWaveform.from_pretrained("suno/bark-small") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): 645cfba
Update README.md
Browse filesconfig should be generation_config
README.md
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```python
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import scipy
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sampling_rate = model.
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scipy.io.wavfile.write("bark_out.wav", rate=sampling_rate, data=speech_values.cpu().numpy().squeeze())
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```
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```python
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import scipy
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sampling_rate = model.generation_config.sample_rate
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scipy.io.wavfile.write("bark_out.wav", rate=sampling_rate, data=speech_values.cpu().numpy().squeeze())
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```
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